The development of an artificial neural network correlation for prediction of rotating magnetic field effects on the process of production of disperse systems Fe3O4–Liquid

In this study an attempt has been made to systemize and develop achievements in the application of artificial neural networks (ANN) to support the modelling of hydrodynamic behaviour of the liquid–ferromagnetic particles systems. The main idea of this paper is the elaboration of new methods to describe the produced ferromagnetic disperse systems by using a rotating magnetic field (RMF). The influence of an RMF on the quality of the obtained predictions probability size distributions (PSD) as well as other aspects, such as the influence of the operational parameters on the development of this modelling approach has been also taken into account in this experimental analysis.